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warehouse-chart-reports

Generate warehouse analytics charts, table images, and report-ready visuals from SQLite/CSV data. Use when the user asks for warehouse charts, product table images, stock health pie charts, revenue/profit visuals, missing-product visuals, or image assets for PDF/slide reporting.

chinmayagit0 来源安装数☆ 0 仓库 Stars
查看来源 ↗安装与使用SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install chinmayagit/warehouse-reports

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

Warehouse Chart Reports

Use this skill to produce clean chart/report images for warehouse demos.

Run full warehouse visual pack (recommended)

Execute:

python skills/warehouse-chart-reports/scripts/run_warehouse_reports.py \
  --db demo/warehouse_agent/warehouse_demo.db \
  --out demo/warehouse_agent/outputs

This generates:

  • stock_status_pie.png
  • revenue_by_category.png
  • daily_profit_30d.png
  • product_table_top40.png
  • missing_products.csv
  • kpi_summary.txt

Generate product table image only

Execute:

python skills/warehouse-chart-reports/scripts/product_table_image.py \
  --db demo/warehouse_agent/warehouse_demo.db \
  --out demo/warehouse_agent/outputs/product_table_top40.png \
  --limit 40

Notes

  • Prefer virtualenv Python when matplotlib is unavailable system-wide.
  • Keep chart style simple and readable for PDF embedding.
  • If sales timestamps are sparse for today, use the 30-day profit chart for trend visibility.

来源信息

Source
github
Repository
openclaw/skills
Path
skills/chinmayagit/warehouse-reports
Version
—
Commit
fe929868f5b759fc45a385290d08a1b18c2ca626
分类来源
rules
状态
active
可见性
public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md
# Warehouse Chart Reports

Use this skill to produce clean chart/report images for warehouse demos.

## Run full warehouse visual pack (recommended)

Execute:

```bash
python skills/warehouse-chart-reports/scripts/run_warehouse_reports.py \
  --db demo/warehouse_agent/warehouse_demo.db \
  --out demo/warehouse_agent/outputs
```

This generates:
- `stock_status_pie.png`
- `revenue_by_category.png`
- `daily_profit_30d.png`
- `product_table_top40.png`
- `missing_products.csv`
- `kpi_summary.txt`

## Generate product table image only

Execute:

```bash
python skills/warehouse-chart-reports/scripts/product_table_image.py \
  --db demo/warehouse_agent/warehouse_demo.db \
  --out demo/warehouse_agent/outputs/product_table_top40.png \
  --limit 40
```

## Notes

- Prefer virtualenv Python when matplotlib is unavailable system-wide.
- Keep chart style simple and readable for PDF embedding.
- If sales timestamps are sparse for today, use the 30-day profit chart for trend visibility.

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